Evidence for phloem loading via the abaxial bundle sheath cells in maize leaves

Single-cell RNA-sequencing provides new insights into the cell-specific expression patterns and transcriptional regulation of photosynthetic genes in bermudagrass leaf blades

As an important warm-season turfgrass species, bermudagrass (Cynodon dactylon L.) flourishes in warm areas around the world due to the existence of the C4 photosynthetic pathway. However, how C4 photosynthesis operates in bermudagrass leaves is still poorly understood. In this study, we performed single-cell RNA-sequencing on 5296 cells from bermudagrass leaf blades. Eight cell clusters corresponding to mesophyll, bundle sheath, epidermis and vascular bundle cells were successfully identified using known cell marker genes. Expression profiling indicated that genes encoding NADP-dependent malic enzymes (NADP-MEs) were highly expressed in bundle sheath cells, whereas NAD-ME genes were weakly expressed in all cell types, suggesting C4 photosynthesis of bermudagrass leaf blades might be NADP-ME type rather than NAD-ME type. The results also indicated that starch synthesis-related genes showed preferential expression in bundle sheath cells, whereas starch degradation-related genes were highly expressed in mesophyll cells, which agrees with the observed accumulation of starch-filled chloroplasts in bundle sheath cells. Gene co-expression analysis further revealed that different families of transcription factors were co-expressed with multiple C4 photosynthesis-related genes, suggesting a complex transcription regulatory network of C4 photosynthesis might exist in bermudagrass leaf blades. These findings collectively provided new insights into the cell-specific expression patterns and transcriptional regulation of photosynthetic genes in bermudagrass.

ScRNA-seq reveals dark- and light-induced differentially expressed gene atlases of seedling leaves in Arachis hypogaea L

Although the regulatory mechanisms of dark and light-induced plant morphogenesis have been broadly investigated, the biological process in peanuts has not been systematically explored on single-cell resolution. Herein, 10 cell clusters were characterized using scRNA-seq-identified marker genes, based on 13 409 and 11 296 single cells from 1-week-old peanut seedling leaves grown under dark and light conditions. 6104 genes and 50 transcription factors (TFs) displayed significant expression patterns in distinct cell clusters, which provided gene resources for profiling dark/light-induced candidate genes. Further pseudo-time trajectory and cell cycle evidence supported that dark repressed the cell division and perturbed normal cell cycle, especially the PORA abundances correlated with 11 TFs highly enriched in mesophyll to restrict the chlorophyllide synthesis. Additionally, light repressed the epidermis cell developmental trajectory extending by inhibiting the growth hormone pathway, and 21 TFs probably contributed to the different genes transcriptional dynamic. Eventually, peanut AHL17 was identified from the profile of differentially expressed TFs, which encoded protein located in the nucleus promoted leaf epidermal cell enlargement when ectopically overexpressed in Arabidopsis through the regulatory phytohormone pathway. Overall, our study presents the different gene atlases in peanut etiolated and green seedlings, providing novel biological insights to elucidate light-induced leaf cell development at the single-cell level.

Advances in Single-Cell Transcriptome Sequencing and Spatial Transcriptome Sequencing in Plants

"Omics" typically involves exploration of the structure and function of the entire composition of a biological system at a specific level using high-throughput analytical methods to probe and analyze large amounts of data, including genomics, transcriptomics, proteomics, and metabolomics, among other types. Genomics characterizes and quantifies all genes of an organism collectively, studying their interrelationships and their impacts on the organism. However, conventional transcriptomic sequencing techniques target population cells, and their results only reflect the average expression levels of genes in population cells, as they are unable to reveal the gene expression heterogeneity and spatial heterogeneity among individual cells, thus masking the expression specificity between different cells. Single-cell transcriptomic sequencing and spatial transcriptomic sequencing techniques analyze the transcriptome of individual cells in plant or animal tissues, enabling the understanding of each cell's metabolites and expressed genes. Consequently, statistical analysis of the corresponding tissues can be performed, with the purpose of achieving cell classification, evolutionary growth, and physiological and pathological analyses. This article provides an overview of the research progress in plant single-cell and spatial transcriptomics, as well as their applications and challenges in plants. Furthermore, prospects for the development of single-cell and spatial transcriptomics are proposed.

Multiome in the Same Cell Reveals the Impact of Osmotic Stress on Arabidopsis Root Tip Development at Single-Cell Level

Cell-specific transcriptional regulatory networks (TRNs) play vital roles in plant development and response to environmental stresses. However, traditional single-cell mono-omics techniques are unable to directly capture the relationships and dynamics between different layers of molecular information within the same cells. While advanced algorithm facilitates merging scRNA-seq and scATAC-seq datasets, accurate data integration remains a challenge, particularly when investigating cell-type-specific TRNs. By examining gene expression and chromatin accessibility simultaneously in 16,670 Arabidopsis root tip nuclei, the TRNs are reconstructed that govern root tip development under osmotic stress. In contrast to commonly used computational integration at cell-type level, 12,968 peak-to-gene linkage is captured at the bona fide single-cell level and construct TRNs at an unprecedented resolution. Furthermore, the unprecedented datasets allow to more accurately reconstruct the coordinated changes of gene expression and chromatin states during cellular state transition. During root tip development, chromatin accessibility of initial cells precedes gene expression, suggesting that changes in chromatin accessibility may prime cells for subsequent differentiation steps. Pseudo-time trajectory analysis reveal that osmotic stress can shift the functional differentiation of trichoblast. Candidate stress-related gene-linked cis-regulatory elements (gl-cCREs) as well as potential target genes are also identified, and uncovered large cellular heterogeneity under osmotic stress.

Best practices for the execution, analysis, and data storage of plant single-cell/nucleus transcriptomics

Single-cell and single-nucleus RNA-sequencing technologies capture the expression of plant genes at an unprecedented resolution. Therefore, these technologies are gaining traction in plant molecular and developmental biology for elucidating the transcriptional changes across cell types in a specific tissue or organ, upon treatments, in response to biotic and abiotic stresses, or between genotypes. Despite the rapidly accelerating use of these technologies, collective and standardized experimental and analytical procedures to support the acquisition of high-quality data sets are still missing. In this commentary, we discuss common challenges associated with the use of single-cell transcriptomics in plants and propose general guidelines to improve reproducibility, quality, comparability, and interpretation and to make the data readily available to the community in this fast-developing field of research.

Current perspectives on the regulatory mechanisms of sucrose accumulation in sugarcane

Sugars transported from leaves (source) to stems (sink) energize cell growth, elongation, and maintenance. which are regulated by a variety of genes. This review reflects progress and prospects in the regulatory mechanism for maximum sucrose accumulation, including the role of sucrose metabolizing enzymes, sugar transporters and the elucidation of post-transcriptional control of sucrose-induced regulation of translation (SIRT) in the accumulation of sucrose. The current review suggests that SIRT is emerging as a significant mechanism controlling Scbzip44 activities in response to endogenous sugar signals (via the negative feedback mechanism). Sucrose-controlled upstream open reading frame (SC-uORF) exists at the 5' leader region of Scbzip44's main ORF, which inhibits sucrose accumulation through post-transcriptional regulatory mechanisms. Sucrose transporters (SWEET1a/4a/4b/13c, TST, SUT1, SUT4 and SUT5) are crucial for sucrose translocation from source to sink. Particularly, SWEET13c was found to be a major contributor to the efflux in the transportation of stems. Tonoplast sugar transporters (TSTs), which import sucrose into the vacuole, suggest their tissue-specific role from source to sink. Sucrose cleavage has generally been linked with invertase isozymes, whereas sucrose synthase (SuSy)-catalyzed metabolism has been associated with biosynthetic processes such as UDP-Glc, cellulose, hemicellulose and other polymers. However, other two key sucrose-metabolizing enzymes, such as sucrose-6-phosphate phosphohydrolase (S6PP) and sucrose phosphate synthase (SPS) isoforms, have been linked with sucrose biosynthesis. These findings suggest that manipulation of genes, such as overexpression of SPS genes and sucrose transporter genes, silencing of the SC-uORF of Scbzip44 (removing the 5' leader region of the main ORF that is called SIRT-Insensitive) and downregulation of the invertase genes, may lead to maximum sucrose accumulation. This review provides an overview of sugarcane sucrose-regulating systems and baseline information for the development of cultivars with higher sucrose accumulation.

spatialHeatmap: visualizing spatial bulk and single-cell assays in anatomical images

Visualizing spatial assay data in anatomical images is vital for understanding biological processes in cell, tissue, and organ organizations. Technologies requiring this functionality include traditional one-at-a-time assays, and bulk and single-cell omics experiments, including RNA-seq and proteomics. The spatialHeatmap software provides a series of powerful new methods for these needs, and allows users to work with adequately formatted anatomical images from public collections or custom images. It colors the spatial features (e.g. tissues) annotated in the images according to the measured or predicted abundance levels of biomolecules (e.g. mRNAs) using a color key. This core functionality of the package is called a spatial heatmap plot. Single-cell data can be co-visualized in composite plots that combine spatial heatmaps with embedding plots of high-dimensional data. The resulting spatial context information is essential for gaining insights into the tissue-level organization of single-cell data, or vice versa. Additional core functionalities include the automated identification of biomolecules with spatially selective abundance patterns and clusters of biomolecules sharing similar abundance profiles. To appeal to both non-expert and computational users, spatialHeatmap provides a graphical and a command-line interface, respectively. It is distributed as a free, open-source Bioconductor package (https://bioconductor.org/packages/spatialHeatmap) that users can install on personal computers, shared servers, or cloud systems.

Single-cell transcriptomics is revolutionizing the improvement of plant biotechnology research: recent advances and future opportunities

Single-cell approaches are a promising way to obtain high-resolution transcriptomics data and have the potential to revolutionize the study of plant growth and development. Recent years have seen the advent of unprecedented technological advances in the field of plant biology to study the transcriptional information of individual cells by single-cell RNA sequencing (scRNA-seq). This review focuses on the modern advancements of single-cell transcriptomics in plants over the past few years. In addition, it also offers a new insight of how these emerging methods will expedite advance research in plant biotechnology in the near future. Lastly, the various technological hurdles and inherent limitations of single-cell technology that need to be conquered to develop such outstanding possible knowledge gain is critically analyzed and discussed.

Plant biotechnology research with single-cell transcriptome: recent advancements and prospects

KEY MESSAGE

Single-cell transcriptomic techniques have emerged as powerful tools in plant biology, offering high-resolution insights into gene expression at the individual cell level. This review highlights the rapid expansion of single-cell technologies in plants, their potential in understanding plant development, and their role in advancing plant biotechnology research. Single-cell techniques have emerged as powerful tools to enhance our understanding of biological systems, providing high-resolution transcriptomic analysis at the single-cell level. In plant biology, the adoption of single-cell transcriptomics has seen rapid expansion of available technologies and applications. This review article focuses on the latest advancements in the field of single-cell transcriptomic in plants and discusses the potential role of these approaches in plant development and expediting plant biotechnology research in the near future. Furthermore, inherent challenges and limitations of single-cell technology are critically examined to overcome them and enhance our knowledge and understanding.

A common regulatory switch controls a suite of C4 traits in multiple cell types

The C4 photosynthetic pathway provided a major advantage to plants growing in hot, dry environments, including the ancestors of our most productive crops. Two traits were essential for the evolution of this pathway: increased vein density and the functionalization of bundle sheath cells for photosynthesis. Although GRAS transcriptional regulators, including SHORT ROOT (SHR), have been implicated in mediating leaf patterning in both C3 and C4 species, little is known about what controls the specialized features of the cells that mediate C4 metabolism and physiology. We show in the model monocot, Setaria viridis, that SHR regulates components of multiple cell identities, including chloroplast biogenesis and photosynthetic gene expression in bundle sheath cells, a central feature of C4 plants. Furthermore, we found that it also contributes to the two-cell compartmentalization of the characteristic four-carbon shuttle pathway. Disruption of SHR function clearly reduced photosynthetic capacity and seed yield in mutant plants under heat stress. Together, these results show how cell identities are remodeled by SHR to host the suite of traits characteristic of C4 regulation, which are a main engineering target in non-C4 crops to improve climate resilience.

Single-cell transcriptomic analysis of pea shoot development and cell-type-specific responses to boron deficiency

Understanding how nutrient stress impacts plant growth is fundamentally important to the development of approaches to improve crop production under nutrient limitation. Here we applied single-cell RNA sequencing to shoot apices of Pisum sativum grown under boron (B) deficiency. We identified up to 15 cell clusters based on the clustering of gene expression profiles and verified cell identity with cell-type-specific marker gene expression. Different cell types responded differently to B deficiency. Specifically, the expression of photosynthetic genes in mesophyll cells (MCs) was down-regulated by B deficiency, consistent with impaired photosynthetic rate. Furthermore, the down-regulation of stomatal development genes in guard cells, including homologs of MUTE and TOO MANY MOUTHS, correlated with a decrease in stomatal density under B deficiency. We also constructed the developmental trajectory of the shoot apical meristem (SAM) cells and a transcription factor interaction network. The developmental progression of SAM to MC was characterized by up-regulation of genes encoding histones and chromatin assembly and remodeling proteins including homologs of FASCIATA1 (FAS1) and SWITCH DEFECTIVE/SUCROSE NON-FERMENTABLE (SWI/SNF) complex. However, B deficiency suppressed their expression, which helps to explain impaired SAM development under B deficiency. These results represent a major advance over bulk-tissue RNA-seq analysis in which cell-type-specific responses are lost and hence important physiological responses to B deficiency are missed. The reported findings reveal strategies by which plants adapt to B deficiency thus offering breeders a set of specific targets for genetic improvement. The reported approach and resources have potential applications well beyond P. sativum species and could be applied to various legumes to improve their adaptability to multiple nutrient or abiotic stresses.

Trade-offs between the accumulation of cuticular wax and jasmonic acid-mediated herbivory resistance in maize

Plants have evolved complex physical and chemical defense systems that allow them to withstand herbivory infestation. Composed of a complex mixture of very-long-chain fatty acids (VLCFAs) and their derivatives, cuticular wax constitutes the first physical line of defense against herbivores. Here, we report the function of Glossy 8 (ZmGL8), which encodes a 3-ketoacyl reductase belonging to the fatty acid elongase complex, in orchestrating wax production and jasmonic acid (JA)-mediated defenses against herbivores in maize (Zea mays). The mutation of GL8 enhanced chemical defenses by activating the JA-dependent pathway. We observed a trade-off between wax accumulation and JA levels across maize glossy mutants and 24 globally collected maize inbred lines. In addition, we demonstrated that mutants defective in cuticular wax biosynthesis in Arabidopsis thaliana and maize exhibit enhanced chemical defenses. Comprehensive transcriptomic and lipidomic analyses indicated that the gl8 mutant confers chemical resistance to herbivores by remodeling VLCFA-related lipid metabolism and subsequent JA biosynthesis and signaling. These results suggest that VLCFA-related lipid metabolism has a critical role in regulating the trade-offs between cuticular wax and JA-mediated chemical defenses.

MINI-AC: inference of plant gene regulatory networks using bulk or single-cell accessible chromatin profiles

Gene regulatory networks (GRNs) represent the interactions between transcription factors (TF) and their target genes. Plant GRNs control transcriptional programs involved in growth, development, and stress responses, ultimately affecting diverse agricultural traits. While recent developments in accessible chromatin (AC) profiling technologies make it possible to identify context-specific regulatory DNA, learning the underlying GRNs remains a major challenge. We developed MINI-AC (Motif-Informed Network Inference based on Accessible Chromatin), a method that combines AC data from bulk or single-cell experiments with TF binding site (TFBS) information to learn GRNs in plants. We benchmarked MINI-AC using bulk AC datasets from different Arabidopsis thaliana tissues and showed that it outperforms other methods to identify correct TFBS. In maize, a crop with a complex genome and abundant distal AC regions, MINI-AC successfully inferred leaf GRNs with experimentally confirmed, both proximal and distal, TF-target gene interactions. Furthermore, we showed that both AC regions and footprints are valid alternatives to infer AC-based GRNs with MINI-AC. Finally, we combined MINI-AC predictions from bulk and single-cell AC datasets to identify general and cell-type specific maize leaf regulators. Focusing on C4 metabolism, we identified diverse regulatory interactions in specialized cell types for this photosynthetic pathway. MINI-AC represents a powerful tool for inferring accurate AC-derived GRNs in plants and identifying known and novel candidate regulators, improving our understanding of gene regulation in plants.

Single-cell RNA sequencing reveals a hierarchical transcriptional regulatory network of terpenoid biosynthesis in cotton secretory glandular cells

Plants can synthesize a wide range of terpenoids in response to various environmental cues. However, the specific regulatory mechanisms governing terpenoid biosynthesis at the cellular level remain largely elusive. In this study, we employed single-cell RNA sequencing to comprehensively characterize the transcriptome profile of cotton leaves and established a hierarchical transcriptional network regulating cell-specific terpenoid production. We observed substantial expression levels of genes associated with the biosynthesis of both volatile terpenes (such as β-caryophyllene and β-myrcene) and non-volatile gossypol-type terpenoids in secretory glandular cells. Moreover, two novel transcription factors, namely GoHSFA4a and GoNAC42, are identified to function downstream of the Gossypium PIGMENT GLAND FORMATION genes. Both transcription factors could directly regulate the expression of terpenoid biosynthetic genes in secretory glandular cells in response to developmental and environmental stimuli. For convenient retrieval of the single-cell RNA sequencing data generated in this study, we developed a user-friendly web server . Our findings not only offer valuable insights into the precise regulation of terpenoid biosynthesis genes in cotton leaves but also provide potential targets for cotton breeding endeavors.

Improving photosynthetic efficiency toward food security: Strategies, advances, and perspectives

Photosynthesis in crops and natural vegetation allows light energy to be converted into chemical energy and thus forms the foundation for almost all terrestrial trophic networks on Earth. The efficiency of photosynthetic energy conversion plays a crucial role in determining the portion of incident solar radiation that can be used to generate plant biomass throughout a growth season. Consequently, alongside the factors such as resource availability, crop management, crop selection, maintenance costs, and intrinsic yield potential, photosynthetic energy use efficiency significantly influences crop yield. Photosynthetic efficiency is relevant to sustainability and food security because it affects water use efficiency, nutrient use efficiency, and land use efficiency. This review focuses specifically on the potential for improvements in photosynthetic efficiency to drive a sustainable increase in crop yields. We discuss bypassing photorespiration, enhancing light use efficiency, harnessing natural variation in photosynthetic parameters for breeding purposes, and adopting new-to-nature approaches that show promise for achieving unprecedented gains in photosynthetic efficiency.

Multi-scale analysis provides insights into the roles of ureide permeases in wheat nitrogen use efficiency

The ureides allantoin and allantoate serve as nitrogen (N) transport compounds in plants, and more recently, allantoin has been shown to play a role in signaling. In planta, tissue ureide levels are controlled by the activity of enzymes of the purine degradation pathway and by ureide transporters called ureide permeases (UPS). Little is known about the physiological function of UPS proteins in crop plants, and especially in monocotyledon species. Here, we identified 13 TaUPS genes in the wheat (Triticum aestivum L.) genome. Phylogenetic and genome location analyses revealed a close relationship of wheat UPSs to orthologues in other grasses and a division into TaUPS1, TaUPS2.1, and TaUPS2.2 groups, each consisting of three homeologs, with a total of four tandem duplications. Expression, localization, and biochemical analyses resolved spatio-temporal expression patterns of TaUPS genes, transporter localization at the plasma membrane, and a role for TaUPS2.1 proteins in cellular import of ureides and phloem and seed loading. In addition, positive correlations between TaUPS1 and TaUPS2.1 transcripts and ureide levels were found. Together the data support that TaUPSs function in regulating ureide pools at source and sink, along with source-to-sink transport. Moreover, comparative studies between wheat cultivars grown at low and high N strengthened a role for TaUPS1 and TaUPS2.1 transporters in efficient N use and in controlling primary metabolism. Co-expression, protein-protein interaction, and haplotype analyses further support TaUPS involvement in N partitioning, N use efficiency, and domestication. Overall, this work provides a new understanding on UPS transporters in grasses as well as insights for breeding resilient wheat varieties with improved N use efficiency.

scPlant: A versatile framework for single-cell transcriptomic data analysis in plants

Single-cell transcriptomics has been fully embraced in plant biological research and is revolutionizing our understanding of plant growth, development, and responses to external stimuli. However, single-cell transcriptomic data analysis in plants is not trivial, given that there is currently no end-to-end solution and that integration of various bioinformatics tools involves a large number of required dependencies. Here, we present scPlant, a versatile framework for exploring plant single-cell atlases with minimum input data provided by users. The scPlant pipeline is implemented with numerous functions for diverse analytical tasks, ranging from basic data processing to advanced demands such as cell-type annotation and deconvolution, trajectory inference, cross-species data integration, and cell-type-specific gene regulatory network construction. In addition, a variety of visualization tools are bundled in a built-in Shiny application, enabling exploration of single-cell transcriptomic data on the fly.

Sugar accumulation enhancement in sorghum stem is associated with reduced reproductive sink strength and increased phloem unloading activity

Sweet sorghum has emerged as a promising source of bioenergy mainly due to its high biomass and high soluble sugar yield in stems. Studies have shown that loss-of-function Dry locus alleles have been selected during sweet sorghum domestication, and decapitation can further boost sugar accumulation in sweet sorghum, indicating that the potential for improving sugar yields is yet to be fully realized. To maximize sugar accumulation, it is essential to gain a better understanding of the mechanism underlying the massive accumulation of soluble sugars in sweet sorghum stems in addition to the Dry locus. We performed a transcriptomic analysis upon decapitation of near-isogenic lines for mutant (d, juicy stems, and green leaf midrib) and functional (D, dry stems and white leaf midrib) alleles at the Dry locus. Our analysis revealed that decapitation suppressed photosynthesis in leaves, but accelerated starch metabolic processes in stems. SbbHLH093 negatively correlates with sugar levels supported by genotypes (DD vs. dd), treatments (control vs. decapitation), and developmental stages post anthesis (3d vs.10d). D locus gene SbNAC074A and other programmed cell death-related genes were downregulated by decapitation, while sugar transporter-encoding gene SbSWEET1A was induced. Both SbSWEET1A and Invertase 5 were detected in phloem companion cells by RNA in situ assay. Loss of the SbbHLH093 homolog, AtbHLH093, in Arabidopsis led to a sugar accumulation increase. This study provides new insights into sugar accumulation enhancement in bioenergy crops, which can be potentially achieved by reducing reproductive sink strength and enhancing phloem unloading.

Exploring plant cis-regulatory elements at single-cell resolution: overcoming biological and computational challenges to advance plant research

Cis-regulatory elements (CREs) are important sequences for gene expression and for plant biological processes such as development, evolution, domestication, and stress response. However, studying CREs in plant genomes has been challenging. The totipotent nature of plant cells, coupled with the inability to maintain plant cell types in culture and the inherent technical challenges posed by the cell wall has limited our understanding of how plant cell types acquire and maintain their identities and respond to the environment via CRE usage. Advances in single-cell epigenomics have revolutionized the field of identifying cell-type-specific CREs. These new technologies have the potential to significantly advance our understanding of plant CRE biology, and shed light on how the regulatory genome gives rise to diverse plant phenomena. However, there are significant biological and computational challenges associated with analyzing single-cell epigenomic datasets. In this review, we discuss the historical and foundational underpinnings of plant single-cell research, challenges, and common pitfalls in the analysis of plant single-cell epigenomic data, and highlight biological challenges unique to plants. Additionally, we discuss how the application of single-cell epigenomic data in various contexts stands to transform our understanding of the importance of CREs in plant genomes.

Opportunities and challenges in the application of single-cell and spatial transcriptomics in plants

Single-cell and spatial transcriptomics have diverted researchers' attention from the multicellular level to the single-cell level and spatial information. Single-cell transcriptomes provide insights into the transcriptome at the single-cell level, whereas spatial transcriptomes help preserve spatial information. Although these two omics technologies are helpful and mature, further research is needed to ensure their widespread applicability in plant studies. Reviewing recent research on plant single-cell or spatial transcriptomics, we compared the different experimental methods used in various plants. The limitations and challenges are clear for both single-cell and spatial transcriptomic analyses, such as the lack of applicability, spatial information, or high resolution. Subsequently, we put forth further applications, such as cross-species analysis of roots at the single-cell level and the idea that single-cell transcriptome analysis needs to be combined with other omics analyses to achieve superiority over individual omics analyses. Overall, the results of this review suggest that combining single-cell transcriptomics, spatial transcriptomics, and spatial element distribution can provide a promising research direction, particularly for plant research.

Application of Multi-Perspectives in Tea Breeding and the Main Directions

Tea plants are an economically important crop and conducting research on tea breeding contributes to enhancing the yield and quality of tea leaves as well as breeding traits that satisfy the requirements of the public. This study reviews the current status of tea plants germplasm resources and their utilization, which has provided genetic material for the application of multi-omics, including genomics and transcriptomics in breeding. Various molecular markers for breeding were designed based on multi-omics, and available approaches in the direction of high yield, quality and resistance in tea plants breeding are proposed. Additionally, future breeding of tea plants based on single-cellomics, pangenomics, plant-microbe interactions and epigenetics are proposed and provided as references. This study aims to provide inspiration and guidance for advancing the development of genetic breeding in tea plants, as well as providing implications for breeding research in other crops.

Spatial expression patterns of genes encoding sugar sensors in leaves of C4 and C3 grasses

BACKGROUND AND AIMS

The mechanisms of sugar sensing in grasses remain elusive, especially those using C4 photosynthesis even though a large proportion of the world's agricultural crops utilize this pathway. We addressed this gap by comparing the expression of genes encoding components of sugar sensors in C3 and C4 grasses, with a focus on source tissues of C4 grasses. Given C4 plants evolved into a two-cell carbon fixation system, it was hypothesized this may have also changed how sugars were sensed.

METHODS

For six C3 and eight C4 grasses, putative sugar sensor genes were identified for target of rapamycin (TOR), SNF1-related kinase 1 (SnRK1), hexokinase (HXK) and those involved in the metabolism of the sugar sensing metabolite trehalose-6-phosphate (T6P) using publicly available RNA deep sequencing data. For several of these grasses, expression was compared in three ways: source (leaf) versus sink (seed), along the gradient of the leaf, and bundle sheath versus mesophyll cells.

KEY RESULTS

No positive selection of codons associated with the evolution of C4 photosynthesis was identified in sugar sensor proteins here. Expressions of genes encoding sugar sensors were relatively ubiquitous between source and sink tissues as well as along the leaf gradient of both C4 and C3 grasses. Across C4 grasses, SnRK1β1 and TPS1 were preferentially expressed in the mesophyll and bundle sheath cells, respectively. Species-specific differences of gene expression between the two cell types were also apparent.

CONCLUSIONS

This comprehensive transcriptomic study provides an initial foundation for elucidating sugar-sensing genes within major C4 and C3 crops. This study provides some evidence that C4 and C3 grasses do not differ in how sugars are sensed. While sugar sensor gene expression has a degree of stability along the leaf, there are some contrasts between the mesophyll and bundle sheath cells.

Development of High-Quality Nuclei Isolation to Study Plant Root-Microbe Interaction for Single-Nuclei Transcriptomic Sequencing in Soybean

Single-nucleus RNA sequencing (sNucRNA-seq) is an emerging technology that has been rapidly adopted and demonstrated to be a powerful tool for detailed characterization of each cell- and sub cell-types in complex tissues of higher eukaryotes. sNucRNA-seq has also been used to dissect cell-type-specific transcriptional responses to environmental or developmental signals. In plants, this technology is being utilized to identify cell-type-specific trajectories for the study of several tissue types and important traits, including the single-cell dissection of the genetic determinants regulating plant-microbe interactions. The isolation of high-quality nuclei is one of the prerequisite steps to obtain high-quality sNucRNA-seq results. Although nuclei isolation from several plant tissues is well established, this process is highly troublesome when plant tissues are associated with beneficial or pathogenic microbes. For example, root tissues colonized with rhizobium bacteria (nodules), leaf tissue infected with bacterial or fungal pathogens, or roots infected with nematodes pose critical challenges to the isolation of high-quality nuclei and use for downstream application. Therefore, isolation of microbe-free, high-quality nuclei from plant tissues are necessary to avoid clogging or interference with the microfluidic channel (e.g., 10× Genomics) or particle-templated emulsion that are used in sNucRNA-seq platforms. Here, we developed a simple, effective, and efficient method to isolate high-quality nuclei from soybean roots and root nodules, followed by washing out bacterial contamination. This protocol has been designed to be easily implemented into any lab environment, and it can also be scaled up for use with multiple samples and applicable to a variety of samples with the presence of microbes. We validated this protocol by successfully generating a barcoded library using the 10× Genomics microfluidic platform from tissue subjected to this procedure. This workflow was developed to provide an accessible alternative to instrument-based approaches (e.g., fluorescent cell sorting) and will expand the ability of researchers to perform experiments such as sNucRNA-seq and sNucATAC-seq on inherently heterogeneous plant tissue samples.

Deciphering plant cell-cell communications using single-cell omics data

Plants have various cell types that respond to different environmental factors, and cell-cell communication is the fundamental process that controls these plant responses. The emergence of single-cell techniques provides opportunities to explore features unique to each cell type and construct a comprehensive cell-cell communication (CCC) network. Although the most current successes of CCC inference were achieved in animal research, computational methods can also be directly applied to plants. This review describes the current major models for cell-cell communication inference and summarizes the computational tools based on single-cell omics datasets. In addition, we discuss the limitations of plant cell-cell communication research and propose new directions to expand the field in meaningful ways.

Single-cell and spatial multi-omics in the plant sciences: Technical advances, applications, and perspectives

Plants contain a large number of cell types and exhibit complex regulatory mechanisms. Studies at the single-cell level have gradually become more common in plant science. Single-cell transcriptomics, spatial transcriptomics, and spatial metabolomics techniques have been combined to analyze plant development. These techniques have been used to study the transcriptomes and metabolomes of plant tissues at the single-cell level, enabling the systematic investigation of gene expression and metabolism in specific tissues and cell types during defined developmental stages. In this review, we present an overview of significant breakthroughs in spatial multi-omics in plants, and we discuss how these approaches may soon play essential roles in plant research.

Single-cell transcriptomic analysis reveals the developmental trajectory and transcriptional regulatory networks of pigment glands in Gossypium bickii

Comprehensive utilization of cottonseeds is limited by the presence of pigment glands and its inclusion gossypol. The ideal cotton has glandless seeds but a glanded plant, a trait found in only a few Australian wild cotton species, including Gossypium bickii. Introgression of this trait into cultivated species has proved to be difficult. Understanding the biological processes toward pigment gland morphogenesis and the associated underlying molecular mechanisms will facilitate breeding of cultivated cotton varieties with the trait of glandless seeds and glanded plant. In this study, single-cell RNA sequencing (scRNA-seq) was performed on 12 222 protoplasts isolated from cotyledons of germinating G. bickii seeds 48 h after imbibition. Clustered into 14 distinct clusters unsupervisedly, these cells could be grouped into eight cell populations with the assistance of known cell marker genes. The pigment gland cells were well separated from others and could be separated into pigment gland parenchyma cells, secretory cells, and apoptotic cells. By integrating the pigment gland cell developmental trajectory, transcription factor regulatory networks, and core transcription factor functional validation, we established a model for pigment gland formation. In this model, light and gibberellin were verified to promote the formation of pigment glands. In addition, three novel genes, GbiERF114 (ETHYLENE RESPONSE FACTOR 114), GbiZAT11 (ZINC FINGER OF ARABIDOPSIS THALIANA 11), and GbiNTL9 (NAC TRANSCRIPTION FACTOR-LIKE 9), were found to affect pigment gland formation. Collectively, these findings provide new insights into pigment gland morphogenesis and lay the cornerstone for future cotton scRNA-seq investigations.

Trehalose 6-phosphate metabolism in C4 species

Trehalose 6-phosphate (Tre6P), the intermediate of trehalose biosynthesis, is an essential signal metabolite in plants, linking growth and development to carbon status. Our current understanding of Tre6P metabolism and signaling pathways in plants is based almost entirely on studies performed with Arabidopsis thaliana, a model plant that performs C₃ photosynthesis. Conversely, our knowledge on the molecular mechanisms involved in Tre6P regulation of carbon partitioning and metabolism in C₄ plants is scarce. This topic is especially relevant due to the agronomic importance of crops performing C₄ photosynthesis, such as maize, sorghum and sugarcane. In this review, we focused our attention on recent developments related to Tre6P metabolism in C₄ species and raised some open questions that should be addressed in the near future to improve the yield of economically important crops.

Upcoming progress of transcriptomics studies on plants: An overview

Transcriptome sequencing or RNA-Sequencing is a high-resolution, sensitive and high-throughput next-generation sequencing (NGS) approach used to study non-model plants and other organisms. In other words, it is an assembly of RNA transcripts from individual or whole samples of functional and developmental stages. RNA-Seq is a significant technique for identifying gene predictions and mining functional analysis that improves gene ontology understanding mechanisms of biological processes, molecular functions, and cellular components, but there is limited information available on this topic. Transcriptomics research on different types of plants can assist researchers to understand functional genes in better ways and regulatory processes to improve breeding selection and cultivation practices. In recent years, several advancements in RNA-Seq technology have been made for the characterization of the transcriptomes of distinct cell types in biological tissues in an efficient manner. RNA-Seq technologies are briefly introduced and examined in terms of their scientific applications. In a nutshell, it introduces all transcriptome sequencing and analysis techniques, as well as their applications in plant biology research. This review will focus on numerous existing and forthcoming strategies for improving transcriptome sequencing technologies for functional gene mining in various plants using RNA- Seq technology, based on the principles, development, and applications.

Unleashing the power within short-read RNA-seq for plant research: Beyond differential expression analysis and toward regulomics

RNA-seq has become a state-of-the-art technique for transcriptomic studies. Advances in both RNA-seq techniques and the corresponding analysis tools and pipelines have unprecedently shaped our understanding in almost every aspects of plant sciences. Notably, the integration of huge amount of RNA-seq with other omic data sets in the model plants and major crop species have facilitated plant regulomics, while the RNA-seq analysis has still been primarily used for differential expression analysis in many less-studied plant species. To unleash the analytical power of RNA-seq in plant species, especially less-studied species and biomass crops, we summarize recent achievements of RNA-seq analysis in the major plant species and representative tools in the four types of application: (1) transcriptome assembly, (2) construction of expression atlas, (3) network analysis, and (4) structural alteration. We emphasize the importance of expression atlas, coexpression networks and predictions of gene regulatory relationships in moving plant transcriptomes toward regulomics, an omic view of genome-wide transcription regulation. We highlight what can be achieved in plant research with RNA-seq by introducing a list of representative RNA-seq analysis tools and resources that are developed for certain minor species or suitable for the analysis without species limitation. In summary, we provide an updated digest on RNA-seq tools, resources and the diverse applications for plant research, and our perspective on the power and challenges of short-read RNA-seq analysis from a regulomic point view. A full utilization of these fruitful RNA-seq resources will promote plant omic research to a higher level, especially in those less studied species.

MINI-EX: Integrative inference of single-cell gene regulatory networks in plants

Multicellular organisms, such as plants, are characterized by highly specialized and tightly regulated cell populations, establishing specific morphological structures and executing distinct functions. Gene regulatory networks (GRNs) describe condition-specific interactions of transcription factors (TFs) regulating the expression of target genes, underpinning these specific functions. As efficient and validated methods to identify cell-type-specific GRNs from single-cell data in plants are lacking, limiting our understanding of the organization of specific cell types in both model species and crops, we developed MINI-EX (Motif-Informed Network Inference based on single-cell EXpression data), an integrative approach to infer cell-type-specific networks in plants. MINI-EX uses single-cell transcriptomic data to define expression-based networks and integrates TF motif information to filter the inferred regulons, resulting in networks with increased accuracy. Next, regulons are assigned to different cell types, leveraging cell-specific expression, and candidate regulators are prioritized using network centrality measures, functional annotations, and expression specificity. This embedded prioritization strategy offers a unique and efficient means to unravel signaling cascades in specific cell types controlling a biological process of interest. We demonstrate the stability of MINI-EX toward input data sets with low number of cells and its robustness toward missing data, and show that it infers state-of-the-art networks with a better performance compared with other related single-cell network tools. MINI-EX successfully identifies key regulators controlling root development in Arabidopsis and rice, leaf development in Arabidopsis, and ear development in maize, enhancing our understanding of cell-type-specific regulation and unraveling the roles of different regulators controlling the development of specific cell types in plants.

Asymmetric wall ingrowth deposition in Arabidopsis phloem parenchyma transfer cells is tightly associated with sieve elements

In Arabidopsis, polarized deposition of wall ingrowths in phloem parenchyma (PP) transfer cells (TCs) occurs adjacent to cells of the sieve element/companion cell (SE/CC) complex. However, the spatial relationships between these different cell types in minor veins, where phloem loading occurs, are poorly understood. PP TC development and wall ingrowth localization were compared with those of other phloem cells in leaves of Col-0 and the transgenic lines AtSUC2::AtSTP9-GFP (green fluorescent protein) and AtSWEET11::AtSWEET11-GFP that identify CCs and PP cells, respectively. The development of PP TCs in minor veins, indicated by deposition of wall ingrowths, proceeded basipetally in leaves. However, not all PP cells develop wall ingrowths, and higher levels of deposition occur in abaxial- compared with adaxial-positioned PP TCs. Furthermore, the deposition of wall ingrowths was exclusively initiated on and preferentially covered the PP TC/SE interface, rather than the PP TC/CC interface, and only occurred in PP cells that were adjacent to SEs. Collectively, these results demonstrate a tight association between SEs and wall ingrowth deposition in PP TCs and suggest the existence of two subtypes of PP cells in leaf minor veins. Compared with PP cells, PP TCs showed more abundant accumulation of AtSWEET11-GFP, indicating functional differences in phloem loading between PP and PP TCs.

Comparison of SWEET gene family between maize and foxtail millet through genomic, transcriptomic, and proteomic analyses

Foxtail millet [Setaria italica (L.) P. Beauv.] does not show high yield and biomass compared with maize (Zea mays L.) although it is a C₄ crop with the potential for high productivity. Because SWEET genes, which are important for sugar transport in plants, play critical roles in biomass production and seed filling in crops, genome-wide, transcriptomic, and proteomic comparison on SWEET gene family between these two species would provide some clues for unlocking this issue. In our study, 24 SWEET genes were identified in foxtail millet and maize. Sequence-based bioinformatics combined with gene expression analyses identified several candidate functional orthologs in these two species. A comparative analysis on expression characteristics of SWEET genes and proteins between maize and foxtail millet indicate that not only some critical major SWEET proteins show significant upregulation in maize compared with their orthologs in foxtail millet, but also there are more quantities of maize SWEET genes showing high expressions than that of foxtail millet genes, suggesting that compared with foxtail millet, maize possesses higher capacity of sugar transport, the crucial determinant for crop yield and biomass. These results provide a basis on revealing why foxtail millet exhibits low yield and biomass although it is a C₄ crop with the potential for high productivity.

Network and epigenetic characterization of subsets of genes specifically expressed in maize bundle sheath cells

Bundle sheath (BS) cells exhibit dramatically structural differences and functional variations at physiological, biochemical and epigenetic levels as compared to mesophyll (M) cells in maize. The regulatory mechanisms controlling functional divergences between M and BS have been extensively investigated. However, BS cell-related regulatory networks are still not completely characterized. To address this, we herein conducted WGCNA-related co-expression assays using bulk M and BS cell RNA-seq data sets and identified a module containing 384 genes highly expressed in BS cells (including 20 hub TFs) instead of M cells. According to the hub TF centered regulatory network, we found that Dof22 and Dof30 might act as key regulators in the regulation of expression of BS-specific genes, and several MYB TFs exhibited a high collaboration with Dof TFs. By comparing the enrichment levels of histone modifications, we found that genes in the aforementioned module were more enriched with histone acetylation as compared to other BS-enriched DEGs with similar expression levels. Moreover, we found that a subset of genes functioning in photosynthesis, protein auto processing and enzymatic activities were significantly enriched with broad H3K4me3. Thus, our study provides evidence showing that regulatory network and histone modifications may play vital roles in the regulation of a subset of genes with important functions in BS cells.

Advances and applications of single-cell omics technologies in plant research

Single-cell sequencing approaches reveal the intracellular dynamics of individual cells and answer biological questions with high-dimensional catalogs of millions of cells, including genomics, transcriptomics, chromatin accessibility, epigenomics, and proteomics data across species. These emerging yet thriving technologies have been fully embraced by the field of plant biology, with a constantly expanding portfolio of applications. Here, we introduce the current technical advances used for single-cell omics, especially single-cell genome and transcriptome sequencing. Firstly, we overview methods for protoplast and nucleus isolation and genome and transcriptome amplification. Subsequently, we use well-executed benchmarking studies to highlight advances made through the application of single-cell omics techniques. Looking forward, we offer a glimpse of additional hurdles and future opportunities that will introduce broad adoption of single-cell sequencing with revolutionary perspectives in plant biology.

When SWEETs Turn Tweens: Updates and Perspectives

Sugar translocation between cells and between subcellular compartments in plants requires either plasmodesmata or a diverse array of sugar transporters. Interactions between plants and associated microorganisms also depend on sugar transporters. The sugars will eventually be exported transporter (SWEET) family is made up of conserved and essential transporters involved in many critical biological processes. The functional significance and small size of these proteins have motivated crystallographers to successfully capture several structures of SWEETs and their bacterial homologs in different conformations. These studies together with molecular dynamics simulations have provided unprecedented insights into sugar transport mechanisms in general and into substrate recognition of glucose and sucrose in particular. This review summarizes our current understanding of the SWEET family, from the atomic to the whole-plant level. We cover methods used for their characterization, theories about their evolutionary origins, biochemical properties, physiological functions, and regulation. We also include perspectives on the future work needed to translate basic research into higher crop yields.

Phloem Loading and Unloading of Sucrose: What a Long, Strange Trip from Source to Sink

Sucrose is transported from sources (mature leaves) to sinks (importing tissues such as roots, stems, fruits, and seeds) through the phloem tissues in veins. In many herbaceous crop species, sucrose must first be effluxed to the cell wall by a sugar transporter of the SWEET family prior to being taken up into phloem companion cells or sieve elements by a different sugar transporter, called SUT or SUC. The import of sucrose into these cells is termed apoplasmic phloem loading. In sinks, sucrose can similarly exit the phloem apoplasmically or, alternatively, symplasmically through plasmodesmata into connecting parenchyma storage cells. Recent advances describing the regulation and manipulation of sugar transporter expression and activities provide stimulating new insights into sucrose phloem loading in sources and unloading processes in sink tissues. Additionally, new breakthroughs have revealed distinct subpopulations of cells in leaves with different functions pertaining to phloem loading. These and other discoveries in sucrose transport are discussed.

Identification of new marker genes from plant single-cell RNA-seq data using interpretable machine learning methods

An essential step in the analysis of single-cell RNA sequencing data is to classify cells into specific cell types using marker genes. In this study, we have developed a machine learning pipeline called single-cell predictive marker (SPmarker) to identify novel cell-type marker genes in the Arabidopsis root. Unlike traditional approaches, our method uses interpretable machine learning models to select marker genes. We have demonstrated that our method can: assign cell types based on cells that were labelled using published methods; project cell types identified by trajectory analysis from one data set to other data sets; and assign cell types based on internal GFP markers. Using SPmarker, we have identified hundreds of new marker genes that were not identified before. As compared to known marker genes, the new marker genes have more orthologous genes identifiable in the corresponding rice single-cell clusters. The new root hair marker genes also include 172 genes with orthologs expressed in root hair cells in five non-Arabidopsis species, which expands the number of marker genes for this cell type by 35-154%. Our results represent a new approach to identifying cell-type marker genes from scRNA-seq data and pave the way for cross-species mapping of scRNA-seq data in plants.

OsSWEET11b, a potential sixth leaf blight susceptibility gene involved in sugar transport-dependent male fertility

SWEETs play important roles in intercellular sugar transport. Induction of SWEET sugar transporters by Transcription Activator-Like effectors (TALe) of Xanthomonas ssp. is key for virulence in rice, cassava and cotton. We identified OsSWEET11b with roles in male fertility and potential bacterial blight (BB) susceptibility in rice. While single ossweet11a or 11b mutants were fertile, double mutants were sterile. As clade III SWEETs can transport gibberellin (GA), a key hormone for spikelet fertility, sterility and BB susceptibility might be explained by GA transport deficiencies. However, in contrast with the Arabidopsis homologues, OsSWEET11b did not mediate detectable GA transport. Fertility and susceptibility therefore are likely to depend on sucrose transport activity. Ectopic induction of OsSWEET11b by designer TALe enabled TALe-free Xanthomonas oryzae pv. oryzae (Xoo) to cause disease, identifying OsSWEET11b as a potential BB susceptibility gene and demonstrating that the induction of host sucrose uniporter activity is key to virulence of Xoo. Notably, only three of six clade III SWEETs are targeted by known Xoo strains from Asia and Africa. The identification of OsSWEET11b is relevant for fertility and for protecting rice against emerging Xoo strains that target OsSWEET11b.

Optimized Transformation and Gene Editing of the B104 Public Maize Inbred by Improved Tissue Culture and Use of Morphogenic Regulators

Plant transformation is a bottleneck for the application of gene editing in plants. In Zea mays (maize), a breakthrough was made using co-transformation of the morphogenic transcription factors BABY BOOM (BBM) and WUSCHEL (WUS) to induce somatic embryogenesis. Together with adapted tissue culture media, this was shown to increase transformation efficiency significantly. However, use of the method has not been reported widely, despite a clear need for increased transformation capacity in academic settings. Here, we explore use of the method for the public maize inbred B104 that is widely used for transformation by the research community. We find that only modifying tissue culture media already boosts transformation efficiency significantly and can reduce the time in tissue culture by 1 month. On average, production of independent transgenic plants per starting embryo increased from 1 to 4% using BIALAPHOS RESISTANCE (BAR) as a selection marker. In addition, we reconstructed the BBM-WUS morphogenic gene cassette and evaluated its functionality in B104. Expression of the morphogenic genes under tissue- and development stage-specific promoters led to direct somatic embryo formation on the scutellum of zygotic embryos. However, eight out of ten resulting transgenic plants showed pleiotropic developmental defects and were not fertile. This undesirable phenotype was positively correlated with the copy number of the morphogenic gene cassette. Use of constructs in which morphogenic genes are flanked by a developmentally controlled Cre/LoxP recombination system led to reduced T-DNA copy number and fertile T0 plants, while increasing transformation efficiency from 1 to 5% using HIGHLY-RESISTANT ACETOLACTATE SYNTHASE as a selection marker. Addition of a CRISPR/Cas9 module confirmed functionality for gene editing applications, as exemplified by editing the gene VIRESCENT YELLOW-LIKE (VYL) that can act as a visual marker for gene editing in maize. The constructs, methods, and insights produced in this work will be valuable to translate the use of BBM-WUS and other emerging morphogenic regulators (MRs) to other genotypes and crops.

Single-Cell RNA Sequencing for Plant Research: Insights and Possible Benefits

In recent years, advances in single-cell RNA sequencing (scRNA-seq) technologies have continued to change our views on biological systems by increasing the spatiotemporal resolution of our analysis to single-cell resolution. Application of scRNA-seq to plants enables the comprehensive characterization of both common and rare cell types and cell states, uncovering new cell types and revealing how cell types relate to each other spatially and developmentally. This review provides an overview of scRNA-seq methodologies, highlights the application of scRNA-seq in plant science, justifies why scRNA-seq is a master player of sequencing, and explains the role of single-cell transcriptomics technologies in environmental stress adaptation, alongside the challenges and prospects of single-cell transcriptomics. Collectively, we put forward a central role of single-cell sequencing in plant research.

Contributions of sugar transporters to crop yield and fruit quality

The flux, distribution, and storage of soluble sugars regulate crop yield in terms of starch, oil, protein, and total carbohydrates, and affect the quality of many horticultural products. Sugar transporters contribute to phloem loading and unloading. The mechanisms of phloem loading have been studied in detail, but the complex and diverse mechanisms of phloem unloading and sugar storage in sink organs are less explored. Unloading and subsequent transport mechanisms for carbohydrates vary in different sink organs. Analyzing the transport and storage mechanisms of carbohydrates in important storage organs, such as cereal seeds, fruits, or stems of sugarcane, will provide information for genetic improvements to increase crop yield and fruit quality. This review discusses current research progress on sugar transporters involved in carbohydrate unloading and storage in sink organs. The roles of sugar transporters in crop yield and the accumulation of sugars are also discussed to highlight their contribution to efficient breeding.

CsSWEET2, a Hexose Transporter from Cucumber (Cucumis sativus L.), Affects Sugar Metabolism and Improves Cold Tolerance in Arabidopsis

Sugars, which are critical osmotic compounds and signalling molecules in plants, and Sugars Will Eventually be Exported Transporters (SWEETs), which constitute a novel family of sugar transporters, play central roles in plant responses to multiple abiotic stresses. In the present study, a member of the SWEET gene family from cucumber (Cucumis sativus L.), CsSWEET2, was identified and characterized. Histochemical analysis of β-glucuronidase expression in transgenic Arabidopsis plants showed that CsSWEET2 is highly expressed in the leaves; subcellular localization indicated that CsSWEET2 proteins are localized in the plasma membrane and endoplasmic reticulum. Heterologous expression assays in yeast demonstrated that CsSWEET2 encodes an energy-independent hexose/H⁺ uniporter that can complement both glucose and fructose transport deficiencies. Compared with wild-type Arabidopsis plants, transgenic Arabidopsis plants overexpressing CsSWEET2 had much lower relative electrolyte leakage levels and were much more resistant to cold stress. Sugar content analysis showed that glucose and fructose levels in the transgenic Arabidopsis plants were significantly higher than those in the wild-type plants. Taken together, our results suggest that, by mediating sugar metabolism and compartmentation, CsSWEET2 plays a vital role in improving plant cold tolerance.

An Efficient and Universal Protoplast Isolation Protocol Suitable for Transient Gene Expression Analysis and Single-Cell RNA Sequencing

The recent advent of single-cell RNA sequencing (scRNA-seq) has enabled access to the developmental landscape of a complex organ by monitoring the differentiation trajectory of every specialized cell type at the single-cell level. A main challenge in this endeavor is dissociating plant cells from the rigid cell walls and some species are recalcitrant to such cellular isolation. Here, we describe the establishment of a simple and efficient protocol for protoplast preparation in Chirita pumila, which includes two consecutive digestion processes with different enzymatic buffers. Using this protocol, we generated viable cell suspensions suitable for an array of expression analyses, including scRNA-seq. The universal application of this protocol was further tested by successfully isolating high-quality protoplasts from multiple organs (petals, fruits, tuberous roots, and gynophores) from representative species on the key branches of the angiosperm lineage. This work provides a robust method in plant science, overcoming barriers to isolating protoplasts in diverse plant species and opens a new avenue to study cell type specification, tissue function, and organ diversification in plants.

Sustainable Intensification of Maize in the Industrial Revolution: Potential of Nitrifying Bacteria and Archaea

Sustainable intensification is a means that proffer a solution to the increasing demand for food without degrading agricultural land. Maize is one of the most important crops in the industrial revolution era, there is a need for its sustainable intensification. This review discusses the role of maize in the industrial revolution, progress toward sustainable production, and the potential of nitrifying bacteria and archaea to achieve sustainable intensification. The era of the industrial revolution (IR) uses biotechnology which has proven to be the most environmentally friendly choice to improve crop yield and nutrients. Scientific research and the global economy have benefited from maize and maize products which are vast. Research on plant growth-promoting microorganisms is on the increase. One of the ways they carry out their function is by assisting in the cycling of geochemical, thus making nutrients available for plant growth. Nitrifying bacteria and archaea are the engineers of the nitrification process that produce nitrogen in forms accessible to plants. They have been identified in the rhizosphere of many crops, including maize, and have been used as biofertilizers. This study's findings could help in the development of microbial inoculum, which could be used to replace synthetic fertilizer and achieve sustainable intensification of maize production during the industrial revolution.

Single-cell genomics revolutionizes plant development studies across scales

Understanding the development of tissues, organs and entire organisms through the lens of single-cell genomics has revolutionized developmental biology. Although single-cell transcriptomics has been pioneered in animal systems, from an experimental perspective, plant development holds some distinct advantages: cells do not migrate in relation to one another, and new organ formation (of leaves, roots, flowers, etc.) continues post-embryonically from persistent stem cell populations known as meristems. For a time, plant studies lagged behind animal or cell culture-based, single-cell approaches, largely owing to the difficulty in dissociating plant cells from their rigid cell walls. Recent intensive development of single-cell and single-nucleus isolation techniques across plant species has opened up a wide range of experimental approaches. This has produced a rapidly expanding diversity of information across tissue types and species, concomitant with the creative development of methods. In this brief Spotlight, we highlight some of the technical developments and how they have led to profiling single-cell genomics in various plant organs. We also emphasize the contribution of single-cell genomics in revealing developmental trajectories among different cell types within plant organs. Furthermore, we present efforts toward comparative analysis of tissues and organs at a single-cell level. Single-cell genomics is beginning to generate comprehensive information relating to how plant organs emerge from stem cell populations.

Single-Cell Transcriptome and Network Analyses Unveil Key Transcription Factors Regulating Mesophyll Cell Development in Maize

Background: Maize mesophyll (M) cells play important roles in various biological processes such as photosynthesis II and secondary metabolism. Functional differentiation occurs during M-cell development, but the underlying mechanisms for regulating M-cell development are largely unknown. Results: We conducted single-cell RNA sequencing (scRNA-seq) to profile transcripts in maize leaves. We then identified coregulated modules by analyzing the resulting pseudo-time-series data through gene regulatory network analyses. WRKY, ERF, NAC, MYB and Heat stress transcription factor (HSF) families were highly expressed in the early stage, whereas CONSTANS (CO)-like (COL) and ERF families were highly expressed in the late stage of M-cell development. Construction of regulatory networks revealed that these transcript factor (TF) families, especially HSF and COL, were the major players in the early and later stages of M-cell development, respectively. Integration of scRNA expression matrix with TF ChIP-seq and Hi-C further revealed regulatory interactions between these TFs and their targets. HSF1 and COL8 were primarily expressed in the leaf bases and tips, respectively, and their targets were validated with protoplast-based ChIP-qPCR, with the binding sites of HSF1 being experimentally confirmed. Conclusions: Our study provides evidence that several TF families, with the involvement of epigenetic regulation, play vital roles in the regulation of M-cell development in maize.

Single-cell genomics in plants: current state, future directions, and hurdles to overcome

Single-cell genomics has the potential to revolutionize the study of plant development and tissue-specific responses to environmental stimuli by revealing heretofore unknown players and gene regulatory processes. Here, I focus on the current state of single-cell genomics in plants, emerging technologies and applications, in addition to outlining possible future directions for experiments. I describe approaches to enable cheaper and larger experiments and technologies to measure multiple types of molecules to better model and understand cell types and their different states and trajectories throughout development. Lastly, I discuss the inherent limitations of single-cell studies and the technological hurdles that need to be overcome to widely apply single-cell genomics in crops to generate the greatest possible knowledge gain.

Single-cell transcriptomics sheds light on the identity and metabolism of developing leaf cells

As the main photosynthetic instruments of vascular plants, leaves are crucial and complex plant organs. A strict organization of leaf mesophyll and epidermal cell layers orchestrates photosynthesis and gas exchange. In addition, water and nutrients for leaf growth are transported through the vascular tissue. To establish the single-cell transcriptomic landscape of these different leaf tissues, we performed high-throughput transcriptome sequencing of individual cells isolated from young leaves of Arabidopsis (Arabidopsis thaliana) seedlings grown in two different environmental conditions. The detection of approximately 19,000 different transcripts in over 1,800 high-quality leaf cells revealed 14 cell populations composing the young, differentiating leaf. Besides the cell populations comprising the core leaf tissues, we identified subpopulations with a distinct identity or metabolic activity. In addition, we proposed cell-type-specific markers for each of these populations. Finally, an intuitive web tool allows for browsing the presented dataset. Our data present insights on how the different cell populations constituting a developing leaf are connected via developmental, metabolic, or stress-related trajectories.

Chromatin and regulatory differentiation between bundle sheath and mesophyll cells in maize

C₄ plants partition photosynthesis enzymes between the bundle sheath (BS) and the mesophyll (M) cells for the better delivery of CO₂ to RuBisCO and to reduce photorespiration. To better understand how C₄ photosynthesis is regulated at the transcriptional level, we performed RNA-seq, ATAC-seq, ChIP-seq and Bisulfite-seq (BS-seq) on BS and M cells isolated from maize leaves. By integrating differentially expressed genes with chromatin features, we found that chromatin accessibility coordinates with epigenetic features, especially H3K27me3 modification and CHH methylation, to regulate cell type-preferentially enriched gene expression. Not only the chromatin-accessible regions (ACRs) proximal to the genes (pACRs) but also the distal ACRs (dACRs) are determinants of cell type-preferentially enriched expression. We further identified cell type-preferentially enriched motifs, e.g. AAAG for BS cells and TGACC/T for M cells, and determined their corresponding transcription factors: DOFs and WRKYs. The complex interaction between cis and trans factors in the preferential expression of C₄ genes was also observed. Interestingly, cell type-preferentially enriched gene expression can be fine-tuned by the coordination of multiple chromatin features. Such coordination may be critical in ensuring the cell type-specific function of key C₄ genes. Based on the observed cell type-preferentially enriched expression pattern and coordinated chromatin features, we predicted a set of functionally unknown genes, e.g. Zm00001d042050 and Zm00001d040659, to be potential key C₄ genes. Our findings provide deep insight into the architectures associated with C₄ gene expression and could serve as a valuable resource to further identify the regulatory mechanisms present in C₄ species.